OWL (Observe, Watch, Listen): Audiovisual Temporal Context for Localizing Actions in Egocentric Videos

Author:

Ramazanova Merey1,Escorcia Victor2,Heilbron Fabian Caba3,Zhao Chen1,Ghanem Bernard1

Affiliation:

1. King Abdullah University of Science and Technology

2. Samsung AI Centre Cambridge

3. Adobe Research

Funder

King Abdullah University of Science and Technology

Publisher

IEEE

Reference53 articles.

1. Temporal Context Network for Activity Localization in Videos

2. Vggsound: A Large-Scale Audio-Visual Dataset

3. Rescaling egocentric vision: Collection, pipeline and challenges for epic-kitchens-100;damen;International Journal of Computer Vision,2021

4. Scaling egocentric vision: The epic-kitchens dataset;damen;Proceedings of the European Conference on Computer Vision (ECCV),2018

5. HACS: Human Action Clips and Segments Dataset for Recognition and Temporal Localization

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1. Multimodal Isotropic Neural Architecture with Patch Embedding;Neural Information Processing;2023-11-14

2. Audiovisual Masked Autoencoders;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

3. Localizing Moments in Long Video Via Multimodal Guidance;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

4. Learning to Identify Critical States for Reinforcement Learning from Videos;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

5. EgoLoc: Revisiting 3D Object Localization from Egocentric Videos with Visual Queries;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

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